This workshop will offer several collaborative activities and projects to develop practical machine learning skills. Participants will be asked to create their first “neuron,” develop a classification project, and then build an ANN network. A discussion session at the end of the workshop will provide an opportunity to discuss what has been learned and explore the topic in greater depth.

This workshop is offered in a hybrid format, meaning that students who are unable to attend in person can participate online via Teams.

Objectives

The workshop will enable them to:

• Understand the basic principles of supervised machine learning
• Identify the stages of a machine learning project (data preparation, choice of platform and architecture, training, evaluation)
• Be able to build a simple classification model with Python.
• Know how to interpret the results of a model (accuracy, confusion matrix)
• Develop their ability to experiment independently using an interactive notebook (Google Colab).

Target audience

Students

Students (BA, MA, Doctorant at Unifr or HES-SO) wanting to develop their skills in machine learning and AI programming.

Prerequisites

• Basic knowledge of Python programming and mathematics
• This workshop is offered in both French and English. 

Responsibles and speakers

Speakers

HEMMANN Florin et ATHEY-FOUGERHOUSE Brice 

Workshops

• Practical introduction to machine learning with Python

  Content	Session 1 : in person Session 2 : online
  Session 1	23.10.2025 from 08:15 to 12:00 PER21 - B205
  Session 2	23.10.2025 from 08:15 to 12:00 PER21 - B205